A hole-machining process planning system for marine engines

Lee, Cheol-Soo; Lee, Jae-Hyun; Kim, Dong-Soo; Heo, Eun-Young; Kim, Dong-Won

doi:10.1016/j.jmsy.2012.10.005

Cited by 16 publications

(2 citation statements)

References 22 publications

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“…The proposed reconfigurable process-planning mathematical scheme scales better with problem size compared with classical process-planning models. Another paper (Lee et al, 2013) describes the construction of a practical CAPP system for hole making that satisfies the specific requirements of marine engine machining. The applied examples (engine block and cylinder header) described in the article are machined using the proposed system.…”

Section: Capp Overviewmentioning

confidence: 99%

Technological process planning by the use of neural networks

Rojek

2016

AIEDAM

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The central objective of the present author's research is to develop a system supporting the design of a technological process (a computer-aided process planning system) that functions similarly to a human expert in the field in question. The use of neural networks makes the creation of such a system possible. The proposed method uses a system of three blocks of neural networks, and involves the creation of neural networks to be used for the selection of machines, tools, and machining parameters. These networks are built for each process operation separately; that is, a set of neural networks is created for each selection. For the construction of models, different types of neural networks (multilayer networks with error backpropagation, radial basis function, and Kohonen) with different structures were employed, and the networks that made the best selections were identified. A method was also developed for the elimination of defects occurring during the production process. When a defect comes to light, this method suggests changes to the technological process, thus improving the quality of that process. Guidelines for the elimination of defects are produced in the form of decision rules. Such a computer-aided process planning system will be especially useful for process engineers who do not yet have sufficient experience in the design of technological processes, or who have only recently joined a particular manufacturing enterprise and are not fully familiar with its machines and other means of production (tools and instrumentation). It should be emphasized that such a system performs an advisory role, and it is always the process engineer who makes the final decision. The neural network models were tested on real data from an enterprise. A computer-aided process planning system based on rules and neural network models enables the intelligent design of technological processes.

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Section: Capp Overviewmentioning

confidence: 99%

Technological process planning by the use of neural networks

Rojek

2016

AIEDAM

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“…Among them, the most effective utilization method of these process data is process reuse. A variety of process reuse technologies have been adopted in manufacturing enterprises to support the improvement of process design efficiency, such as group technology-based process reuse [5], template-based process reuse [6][7][8][9] and case-based process reuse [10,11].…”

Section: Introductionmentioning

confidence: 99%

Efficient NC process scheme generation method based on reusable macro and micro process fusion

Huang

et al. 2022

Int J Adv Manuf Technol

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Process reuse technology has been widely studied and applied in manufacturing industry. However, the current NC process reuse generally assumes that the micro process is compatible with the macro process, but in fact, the reusable processes from the similar local structures of multiple parts are usually difficult to be compatible with each other under the overall manufacturing requirements of the query parts, which leads to the fact that a large amount of user interactions are still required for modification and adjustment in practical engineering applications, so it is not significant to improve the design efficiency. Therefore, an efficient NC process scheme generation method based on reusable macro and micro process fusion is proposed in this paper. Firstly, according to the calculation of semantic distance of process design intention, the micro processes are mapped to the macro process to realize the fusion of the macro process and the micro process, and a compatibility credibility evaluation model is established to evaluate the compatibility of fusion results. Then, when the fusion result is credible, the machining areas corresponding to the process scheme are adjusted and optimized from the geometric level. The adjustment and optimization of machining areas mainly realize the integration of machining areas and the optimization of machining sequence. Finally, the effectiveness and feasibility of the proposed method are verified by the test of actual parts.

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